Rmodelpriors: Prior specification for model hyperparameters

In oswaldogressani/EpiLPS: A Fast and Flexible Bayesian Tool for Estimating Epidemiological Parameters

Prior specification for model hyperparameters

Description

Specification of the hyperparameters for the Gamma prior on the roughness penalty parameter associated to the P-spline model and the Gamma prior on the overdispersion parameter of the negative binomial model underlying the incidence data.

Usage

Rmodelpriors(
  listcontrol = list(a_delta = 10, b_delta = 10, phi = 2, a_rho = 1e-04, b_rho = 1e-04)
)

Arguments

listcontrol

A list specifying the hyperparameters in the Gamma priors for the roughness penalty parameter of the P-spline model (named a_{\delta}, b_{\delta} and \phi) and the overdispersion parameter of the negative binomial model for the incidence data (named a_{\rho} and b_{\rho}).

Value

A list with the specified hyperparameter components. By default, a_{\delta} = b_{\delta} = 10, \phi = 2 and a_{\rho}=b_{\rho}=10^{-4}.

Author(s)

Oswaldo Gressani [e-mail]

References

Gressani, O., Wallinga, J., Althaus, C. L., Hens, N. and Faes, C. (2022). EpiLPS: A fast and flexible Bayesian tool for estimation of the time-varying reproduction number. Plos Computational Biology, 18(10): e1010618.

oswaldogressani/EpiLPS documentation built on March 12, 2024, 2:20 a.m.